Analyse statistique de données de chaînage à partir du PMSI

National audienc

Analyse statistique de données de chaînage à partir du PMSI

National audienc

Discovery of patient pathways from a national hospital database using process mining and integer linear programming

International audienceThe analysis of patient pathways from event log is gaining importance in the field of medical information. It provides deep insights about the care process and the ways to improve it. This paper combines optimization and process mining. A new Integer Linear Programming model is proposed to discover the care process at a macroscopic scale from a large-size database. When dealing with health-care data, the main challenge to overcome is the considerable variability of patients' behaviors. An original size constraint and an aggregation method are used to create simple but significant process models. The results of a case study on heart failures confirm the ability of the approach to reveal the process information behind the data

Stochastic simulation of clinical pathways from raw health databases

International audienceThis paper presents a method to automatically create stochastic simulation models of clinical pathways from raw databases. We introduce an automatic procedure to convert a process model, discovered with process mining, into an actionable simulation model. The concept of state charts is used and enriched to incorporate the distinctive features of healthcare processes into the model. The clinical pathway model is used to simulate new patients' sequence of events. The resulting model is validated by comparing key performances indicators with historical data. Finally, we use the model to perform an automatically setup sensitivity analysis. The whole process is automated and can be used with any input data

Post procedural pregnancy occurrence risk after endometrial ablation: Pregnancy after endometrial ablation

International audienceObjective: The objective of the study was to analyse the pregnancy rate after curettage, 1G (Endometrial resection) and 2G (Endometrial ablation) procedures in women with abnormal uterine bleeding (AUB-O,E,N) to evaluate the rate of pregnancy following these procedures and to improve pre and post-therapeutic women information. Methods: This retrospective study analyzed data extracted from the French Hospital medical information database. All hospital stays with a diagnostic code for AUB and an appropriate surgical procedure coded between 2009 and 2015 were identified. A total of 109,884 women were included. Of these, 88,165 were followed up for 18 months, 80,054 for 24 months and 33,251 for 60 months. Outcomes were compared between second generation (2G) procedures, first-generation (1G) procedures (endometrial resection) and curettage. The rate of pregnancy was the primary end point. Results: 7863 women underwent a 2G surgical procedure (7.2%), 39,935 a 1G procedure (36.3%) and 38,923 a curettage (35.4%). The mean age of the women was 46 years (IC.95: 36.7-52.5), with no difference in age between groups. The rate of pregnancy after 2G, 1G and curettage was respectively 13 (1.5%), 617 (10.1%) and 1025 (11.1%). The primary endpoint was significantly different between 2G and 1G and curettage (p<0.0001) Conclusion: 2G procedures result in lower risk of pregnancy without requiring specific training for surgeons. However, endometrial ablation cannot be considered as a sterilization method nor an effective contraceptive procedure. In the absence of sterilization of either partner, women should continue to use contraception whatever their age and menstrual status

Impact of hospitalized vaso-occlusive crises in the previous calendar year on mortality and complications in adults with sickle cell disease: a French population-based studyResearch in context

Summary: Background: Historically, sickle cell disease (SCD) patients experiencing frequent hospitalized vaso-occlusive crises (HVOC) have been associated with increased mortality, yet recent data reflecting the widespread use of hydroxyurea and advancements in disease management remain limited. Our study aims to assess the association between HVOC and mortality or severe complications in patients with SCD in this new treatment landscape. Methods: This was a retrospective observational cohort study using the French national health data system. Between 01-01-2012 and 12-31-2018, all SCD patients ≥16 years old (ICD-10 codes D57.0–2) were included and followed until 12-31-2018. HVOC was defined as a hospitalization of ≥1 night with primary diagnosis of SCD with crisis, following an emergency room visit. The association between HVOC and severe complications was assessed with a Cox proportional hazards model. Findings: In total, 8018 patients (56.6% females; 4538/8018) were included. The 2018 SCD standardized one-year period prevalence was 17.9 cases/100,000 person-years [17.4; 18.3]. The mean rate was 0.84 (1.88) HVOC/person-year. In 2018, 70% (5323/7605), 22% (1671/7605), and 8% (611/7605) of patients experienced 0, 1–2, or 3+ HVOCs, respectively. The median survival time between HVOCs was 415 days [386; 439]. Overall, 312 patients died (3.9%) with a mean age of 49.8 (19.4). Compared to patients without HVOC, the hazard ratios of death in patients with 1–2 or 3+ HVOCs the year prior to death were 1.67 [1.21; 2.30] and 3.70 [2.30; 5.93], respectively. Incidence of acute chest syndrome, pulmonary embolism, osteonecrosis, and sepsis increased with the HVOCs category, but not stroke. In 2018, 29.5% (180/611) of patients with 3+ HVOCs did not take hydroxyurea. Interpretation: Patients must be closely monitored during their hospitalizations to intensify treatment and check treatment compliance. Innovative therapies are also required. Funding: The study was funded by Novartis

An optimization-based process mining approach for explainable classification of timed event logs

International audienc

Automatic and Explainable Labeling of Medical Event Logs with Autoencoding

International audienceProcess mining is a suitable method for knowledge extraction from patient pathways. Structured in event logs, medical events are complex, often described using various medical codes. An efficient labeling of these events before applying process mining analysis is challenging. This paper presents an innovative methodology to handle the complexity of events in medical event logs. Based on autoencoding, accurate labels are created by clustering similar events in latent space. Moreover, the explanation of created labels is provided by the decoding of its corresponding events. Tested on synthetic events, the method is able to find hidden clusters on sparse binary data, as well as accurately explain created labels. A case study on real healthcare data is performed. Results confirm the suitability of the method to extract knowledge from complex event logs representing patient pathways

Optimal Process Mining of Timed Event Logs

International audienceThe problem of determining the optimal process model of an event log of traces of events with temporal information is presented. A formal description of the event log and relevant complexity measures are detailed. Then the process model and its replayability score that measures model fitness with respect to the event log are defined. Two process models are formulated, taking into account temporal information. The first, called grid process model, is reminiscent of Petri net unfolding and is a graph with multiple layers of labeled nodes and arcs connecting lower to upper layer nodes. Our second model is an extension of the first. Denoted the time grid process model, it associates a time interval to each arc. Subsequently, a Tabu search algorithm is constructed to determine the optimal process model that maximizes the replayability score subject to the constraints of the maximal number of nodes and arcs. Numerical experiments are conducted to assess the performance of the proposed Tabu search algorithm. Lastly, a healthcare case study was conducted to demonstrate the applicability of our approach for clinical pathway modeling. Special attention was paid on readability, so that final users could beneficially use the process mining results